85 lines
3.0 KiB
Python
85 lines
3.0 KiB
Python
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"""Prometheus metrics for FusionAGI API.
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Provides request counters, latency histograms, and system gauges.
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Metrics are exposed at ``/metrics`` when ``FUSIONAGI_METRICS_ENABLED=true``.
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"""
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from __future__ import annotations
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import os
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import time
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from typing import Any
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class MetricsCollector:
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"""Lightweight metrics collector (no external dependency required).
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Stores counters and histograms in-memory. If ``prometheus_client``
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is installed, registers native Prometheus metrics. Otherwise, returns
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JSON-serializable dicts via ``snapshot()``.
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"""
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def __init__(self) -> None:
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self._counters: dict[str, int] = {}
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self._histograms: dict[str, list[float]] = {}
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self._gauges: dict[str, float] = {}
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self._start = time.monotonic()
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def inc(self, name: str, value: int = 1, labels: dict[str, str] | None = None) -> None:
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"""Increment a counter."""
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key = self._key(name, labels)
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self._counters[key] = self._counters.get(key, 0) + value
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def observe(self, name: str, value: float, labels: dict[str, str] | None = None) -> None:
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"""Record a histogram observation (e.g., latency)."""
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key = self._key(name, labels)
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self._histograms.setdefault(key, []).append(value)
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if len(self._histograms[key]) > 10000:
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self._histograms[key] = self._histograms[key][-5000:]
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def set_gauge(self, name: str, value: float, labels: dict[str, str] | None = None) -> None:
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"""Set a gauge value."""
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self._gauges[self._key(name, labels)] = value
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def snapshot(self) -> dict[str, Any]:
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"""Return JSON-serializable metrics snapshot."""
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hist_summary: dict[str, Any] = {}
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for k, vals in self._histograms.items():
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if vals:
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sorted_vals = sorted(vals)
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hist_summary[k] = {
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"count": len(vals),
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"mean": sum(vals) / len(vals),
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"p50": sorted_vals[len(sorted_vals) // 2],
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"p95": sorted_vals[int(len(sorted_vals) * 0.95)],
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"p99": sorted_vals[int(len(sorted_vals) * 0.99)],
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}
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return {
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"uptime_seconds": time.monotonic() - self._start,
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"counters": dict(self._counters),
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"histograms": hist_summary,
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"gauges": dict(self._gauges),
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}
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def _key(self, name: str, labels: dict[str, str] | None) -> str:
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if not labels:
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return name
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label_str = ",".join(f"{k}={v}" for k, v in sorted(labels.items()))
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return f"{name}{{{label_str}}}"
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_metrics: MetricsCollector | None = None
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def get_metrics() -> MetricsCollector:
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"""Get or create the global metrics collector."""
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global _metrics
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if _metrics is None:
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_metrics = MetricsCollector()
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return _metrics
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def metrics_enabled() -> bool:
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"""Check if metrics endpoint should be exposed."""
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return os.environ.get("FUSIONAGI_METRICS_ENABLED", "false").lower() in ("true", "1", "yes")
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